Classical direct marketing, which really became big in the 1990s, has historically had a very "campaign management" approach. Here, marketers would design their campaigns, perhaps as much as a year in advance. These campaigns were defined in terms of budgets, objectives, time frames, etc. For example, a typical catalog company may run 12-18 campaigns per year. These were costly, expensive processes, designed to deliver the message (in this case the catalog) to exactly the right customer or prospect most likely to respond. (I junk the customer/prospect triage for the remainder of this post, preferring instead the generic consumer).
Many companies made lots of money figuring out how to help marketers optimize these types of campaigns, including consultants, service bureas, lettershops, etc.
This approach seems quaint and laughable just 10 years later, Simply, digital media has done two things. First, it has expanded the addressability of consumers from a house to many locations (think multiple email addresses, social media profiles, sms, set top box, you name it). Second, is has highlighted the need for speed in marketing. Simply, campaigns planned months in advance to an audience of 1 (not talking brand marketing but direct marketing) have no chance of success anymore. Today, it is not about which consumers you do not talk to, but how you do engage with each one with which you would like to engage!
So back to the question, how does DM take advantage of social media, and evolve? I believe that one can blend the best of old and new concepts in an integrated approach that works.
So what works from the old direct marketing?
1) Advanced and sophisticated modeling works. For all the real time recommendation engines deployed by Amazon or Omniture et al, nothing beats a detailed historical review of all consumer data to determine the optimal offer to present to that consumer. While real time web visit behavior is an important element to blend in, the overall view of that consumer from a behavioral perspective must be incorporated. Without that, too many offers are ignored by that consumer, and these recommendation engines fail to engage those same consumers.
2) Data is key. And this is the good news. All (or most) social media sites generate mountains of data. Their APIs are generally clear, and accessible to even the most novice Javascript programmer. Combining these types of data with more traditional off-line data (transactional history, promotion history and individual level demographics) makes for a powerful combination for our analysts to mine.
3) Good copy wins. I believe that this will never change. From writing multi-page direct mail letters to short Google ads, good copy wins. The next time you search something on Google, see what catches your eye from the available ads. What is interesting to watch will be the ability to tailor the message more and more to the individual as the semantic web unfolds. We can message at the segment level today, and are eying more real time construction of messages to individual consumers.
So next up next time is a discussion on B2B uses of social tools, and I will follow with a discussion on B2C implications for direct marketing.
Thanks for listening.
